OpenRaiser/Intern-Atlas huggingface dataset:
On sparsity averaging
Venue: arXiv cs.IT 2013
Year: 2013

Recent developments in Carrillo et al. (2012) and Carrillo et al. (2013) introduced a novel regularization method for compressive imaging in the context of compressed sensing with coherent redundant dictionaries. The approach relies on the observation that natural images exhibit strong average sparsity over multiple coherent frames. The associated reconstruction algorithm, based on an analysis prior and a reweighted $\ell_1$ scheme, is dubbed Sparsity Averaging Reweighted Analysis (SARA). We review these advances and extend associated simulations establishing the superiority of SARA to regularization methods based on sparsity in a single frame, for a generic spread spectrum acquisition and for a Fourier acquisition of particular interest in radio astronomy.
Systems Dynamics or Agent-Based Modelling for Immune Simulation?
Venue: arXiv cs.CE 2013
Year: 2013

In immune system simulation there are two competing simulation approaches: System Dynamics Simulation (SDS) and Agent-Based Simulation (ABS). In the literature there is little guidance on how to choose the best approach for a specific immune problem. Our overall research aim is to develop a framework that helps researchers with this choice. In this paper we investigate if it is possible to easily convert simulation models between approaches. With no explicit guidelines available from the literature we develop and test our own set of guidelines for converting SDS models into ABS models in a non-spacial scenario. We also define guidelines to convert ABS into SDS considering a non-spatial and a spatial scenario. After running some experiments with the developed models we found that in all cases there are significant differences between the results produced by the different simulation methods.
On string matching with k mismatches
Venue: arXiv cs.DS 2013
Year: 2013

In this paper we consider several variants of the pattern matching problem. In particular, we investigate the following problems: 1) Pattern matching with k mismatches; 2) Approximate counting of mismatches; and 3) Pattern matching with mismatches. The distance metric used is the Hamming distance. We present some novel algorithms and techniques for solving these problems. Both deterministic and randomized algorithms are offered. Variants of these problems where there could be wild cards in either the text or the pattern or both are considered. An experimental evaluation of these algorithms is also presented. The source code is available at http://www.engr.uconn.edu/~man09004/kmis.zip.
Modelling the Effects of User Learning on Forced Innovation Diffusion
Venue: arXiv cs.CY 2013
Year: 2013

Technology adoption theories assume that users' acceptance of an innovative technology is on a voluntary basis. However, sometimes users are force to accept an innovation. In this case users have to learn what it is useful for and how to use it. This learning process will enable users to transit from zero knowledge about the innovation to making the best use of it. So far the effects of user learning on technology adoption have received little research attention. In this paper - for the first time - we investigate the effects of user learning on forced innovation adoption by using an agent-based simulation approach using the case of forced smart metering deployments in the city of Leeds
Intelligent Hybrid Man-Machine Translation Quality Estimation
Venue: arXiv cs.CL 2013
Year: 2013

Inferring evaluation scores based on human judgments is invaluable compared to using current evaluation metrics which are not suitable for real-time applications e.g. post-editing. However, these judgments are much more expensive to collect especially from expert translators, compared to evaluation based on indicators contrasting source and translation texts. This work introduces a novel approach for quality estimation by combining learnt confidence scores from a probabilistic inference model based on human judgments, with selective linguistic features-based scores, where the proposed inference model infers the credibility of given human ranks to solve the scarcity and inconsistency issues of human judgments. Experimental results, using challenging language-pairs, demonstrate improvement in correlation with human judgments over traditional evaluation metrics.
Discovering Stock Price Prediction Rules of Bombay Stock Exchange Using Rough Fuzzy Multi Layer Perception Networks
Venue: arXiv cs.AI 2013
Year: 2013

In India financial markets have existed for many years. A functionally accented, diverse, efficient and flexible financial system is vital to the national objective of creating a market driven, productive and competitive economy. Today markets of varying maturity exist in equity, debt, commodities and foreign exchange. In this work we attempt to generate prediction rules scheme for stock price movement at Bombay Stock Exchange using an important Soft Computing paradigm viz., Rough Fuzzy Multi Layer Perception. The use of Computational Intelligence Systems such as Neural Networks, Fuzzy Sets, Genetic Algorithms, etc. for Stock Market Predictions has been widely established. The process is to extract knowledge in the form of rules from daily stock movements. These rules can then be used to guide investors. To increase the efficiency of the prediction process, Rough Sets is used to discretize the data. The methodology uses a Genetic Algorithm to obtain a structured network suitable for both classification and rule extraction. The modular concept, based on divide and conquer strategy, provides accelerated training and a compact network suitable for generating a minimum number of rules with high certainty values. The concept of variable mutation operator is introduced for preserving the localized structure of the constituting Knowledge Based sub-networks, while they are integrated and evolved. Rough Set Dependency Rules are generated directly from the real valued attribute table containing Fuzzy membership values. The paradigm is thus used to develop a rule extraction algorithm. The extracted rules are compared with some of the related rule extraction techniques on the basis of some quantitative performance indices. The proposed methodology extracts rules which are less in number, are accurate, have high certainty factor and have low confusion with less computation time.
Achieving greater Explanatory Power and Forecasting Accuracy with Non-uniform spread Fuzzy Linear Regression
Venue: arXiv cs.AI 2013
Year: 2013

Fuzzy regression models have been applied to several Operations Research applications viz., forecasting and prediction. Earlier works on fuzzy regression analysis obtain crisp regression coefficients for eliminating the problem of increasing spreads for the estimated fuzzy responses as the magnitude of the independent variable increases. But they cannot deal with the problem of non-uniform spreads. In this work, a three-phase approach is discussed to construct the fuzzy regression model with non-uniform spreads to deal with this problem. The first phase constructs the membership functions of the least-squares estimates of regression coefficients based on extension principle to completely conserve the fuzziness of observations. They are then defuzzified by the centre of area method to obtain crisp regression coefficients in the second phase. Finally, the error terms of the method are determined by setting each estimated spread equal to its corresponding observed spread. The Tagaki-Sugeno inference system is used for improving the accuracy of forecasts. The simulation example demonstrates the strength of fuzzy linear regression model in terms of higher explanatory power and forecasting performance.
Optimal Locally Repairable Linear Codes
Venue: arXiv cs.IT 2013
Year: 2013

Linear erasure codes with local repairability are desirable for distributed data storage systems. An [n, k, d] code having all-symbol (r, δ})-locality, denoted as (r, δ)a, is considered optimal if it also meets the minimum Hamming distance bound. The existing results on the existence and the construction of optimal (r, δ)a codes are limited to only the special case of δ = 2, and to only two small regions within this special case, namely, m = 0 or m >= (v+δ-1) > (δ-1), where m = n mod (r+δ-1) and v = k mod r. This paper investigates the existence conditions and presents deterministic constructive algorithms for optimal (r, δ)a codes with general r and δ. First, a structure theorem is derived for general optimal (r, δ)a codes which helps illuminate some of their structure properties. Next, the entire problem space with arbitrary n, k, r and δ is divided into eight different cases (regions) with regard to the specific relations of these parameters. For two cases, it is rigorously proved that no optimal (r, δ)a could exist. For four other cases the optimal (r, δ)a codes are shown to exist, deterministic constructions are proposed and the lower bound on the required field size for these algorithms to work is provided. Our new constructive algorithms not only cover more cases, but for the same cases where previous algorithms exist, the new constructions require a considerably smaller field, which translates to potentially lower computational complexity. Our findings substantially enriches the knowledge on (r, δ)a codes, leaving only two cases in which the existence of optimal codes are yet to be determined.
Finding the creatures of habit; Clustering households based on their flexibility in using electricity
Venue: arXiv cs.LG 2013
Year: 2013

Changes in the UK electricity market, particularly with the roll out of smart meters, will provide greatly increased opportunities for initiatives intended to change households' electricity usage patterns for the benefit of the overall system. Users show differences in their regular behaviours and clustering households into similar groupings based on this variability provides for efficient targeting of initiatives. Those people who are stuck into a regular pattern of activity may be the least receptive to an initiative to change behaviour. A sample of 180 households from the UK are clustered into four groups as an initial test of the concept and useful, actionable groupings are found.
On Negotiation as Concurrency Primitive
Venue: arXiv cs.LO 2013
Year: 2013

We introduce negotiations, a model of concurrency close to Petri nets, with multiparty negotiation as primitive. We study the problems of soundness of negotiations and of, given a negotiation with possibly many steps, computing a summary, i.e., an equivalent one-step negotiation. We provide a complete set of reduction rules for sound, acyclic, weakly deterministic negotiations and show that, for deterministic negotiations, the rules compute the summary in polynomial time.
The MacWilliams identity for $m$-spotty weight enumerator over $\mathbb{F}_2+u\mathbb{F}_2+\cdots+u^{m-1}\mathbb{F}_2$
Venue: arXiv cs.IT 2013
Year: 2013

Past few years have seen an extensive use of RAM chips with wide I/O data (e.g. 16, 32, 64 bits) in computer memory systems. These chips are highly vulnerable to a special type of byte error, called an $m$-spotty byte error, which can be effectively detected or corrected using byte error-control codes. The MacWilliams identity provides the relationship between the weight distribution of a code and that of its dual. The main purpose of this paper is to present a version of the MacWilliams identity for $m$-spotty weight enumerators over $\mathbbm{F}_{2}+u\mathbbm{F}_{2}+\cdots+u^{m-1}\mathbbm{F}_{2}$ (shortly $R_{u, m, 2}$).
From bounded affine types to automatic timing analysis
Venue: arXiv cs.PL 2013
Year: 2013

Bounded linear types have proved to be useful for automated resource analysis and control in functional programming languages. In this paper we introduce an affine bounded linear typing discipline on a general notion of resource which can be modeled in a semiring. For this type system we provide both a general type-inference procedure, parameterized by the decision procedure of the semiring equational theory, and a (coherent) categorical semantics. This is a very useful type-theoretic and denotational framework for many applications to resource-sensitive compilation, and it represents a generalization of several existing type systems. As a non-trivial instance, motivated by our ongoing work on hardware compilation, we present a complex new application to calculating and controlling timing of execution in a (recursion-free) higher-order functional programming language with local store.
Fault Tolerant Clustering Revisited
Venue: arXiv cs.DS 2013
Year: 2013

In discrete k-center and k-median clustering, we are given a set of points P in a metric space M, and the task is to output a set C \subseteq ? P, |C| = k, such that the cost of clustering P using C is as small as possible. For k-center, the cost is the furthest a point has to travel to its nearest center, whereas for k-median, the cost is the sum of all point to nearest center distances. In the fault-tolerant versions of these problems, we are given an additional parameter 1 ?\leq \ell \leq ? k, such that when computing the cost of clustering, points are assigned to their \ell-th nearest-neighbor in C, instead of their nearest neighbor. We provide constant factor approximation algorithms for these problems that are both conceptually simple and highly practical from an implementation stand-point.
Point Line Cover: The Easy Kernel is Essentially Tight
Venue: arXiv cs.DS 2013
Year: 2013

The input to the NP-hard Point Line Cover problem (PLC) consists of a set $P$ of $n$ points on the plane and a positive integer $k$, and the question is whether there exists a set of at most $k$ lines which pass through all points in $P$. A simple polynomial-time reduction reduces any input to one with at most $k^2$ points. We show that this is essentially tight under standard assumptions. More precisely, unless the polynomial hierarchy collapses to its third level, there is no polynomial-time algorithm that reduces every instance $(P,k)$ of PLC to an equivalent instance with $O(k^{2-ε})$ points, for any $ε>0$. This answers, in the negative, an open problem posed by Lokshtanov (PhD Thesis, 2009). Our proof uses the machinery for deriving lower bounds on the size of kernels developed by Dell and van Melkebeek (STOC 2010). It has two main ingredients: We first show, by reduction from Vertex Cover, that PLC---conditionally---has no kernel of total size $O(k^{2-ε})$ bits. This does not directly imply the claimed lower bound on the number of points, since the best known polynomial-time encoding of a PLC instance with $n$ points requires $ω(n^{2})$ bits. To get around this we build on work of Goodman et al. (STOC 1989) and devise an oracle communication protocol of cost $O(n\log n)$ for PLC; its main building block is a bound of $O(n^{O(n)})$ for the order types of $n$ points that are not necessarily in general position, and an explicit algorithm that enumerates all possible order types of n points. This protocol and the lower bound on total size together yield the stated lower bound on the number of points. While a number of essentially tight polynomial lower bounds on total sizes of kernels are known, our result is---to the best of our knowledge---the first to show a nontrivial lower bound for structural/secondary parameters.
Secure and Policy-Private Resource Sharing in an Online Social Network
Venue: arXiv cs.CR 2013
Year: 2013

Providing functionalities that allow online social network users to manage in a secure and private way the publication of their information and/or resources is a relevant and far from trivial topic that has been under scrutiny from various research communities. In this work, we provide a framework that allows users to define highly expressive access policies to their resources in a way that the enforcement does not require the intervention of a (trusted or not) third party. This is made possible by the deployment of a newly defined cryptographic primitives that provides - among other things - efficient access revocation and access policy privacy. Finally, we provide an implementation of our framework as a Facebook application, proving the feasibility of our approach.
Flow-Based Algorithms for Local Graph Clustering
Venue: arXiv cs.DS 2013
Year: 2013

Given a subset S of vertices of an undirected graph G, the cut-improvement problem asks us to find a subset S that is similar to A but has smaller conductance. A very elegant algorithm for this problem has been given by Andersen and Lang [AL08] and requires solving a small number of single-commodity maximum flow computations over the whole graph G. In this paper, we introduce LocalImprove, the first cut-improvement algorithm that is local, i.e. that runs in time dependent on the size of the input set A rather than on the size of the entire graph. Moreover, LocalImprove achieves this local behaviour while essentially matching the same theoretical guarantee as the global algorithm of Andersen and Lang. The main application of LocalImprove is to the design of better local-graph-partitioning algorithms. All previously known local algorithms for graph partitioning are random-walk based and can only guarantee an output conductance of O(\sqrt{OPT}) when the target set has conductance OPT \in [0,1]. Very recently, Zhu, Lattanzi and Mirrokni [ZLM13] improved this to O(OPT / \sqrt{CONN}) where the internal connectivity parameter CONN \in [0,1] is defined as the reciprocal of the mixing time of the random walk over the graph induced by the target set. In this work, we show how to use LocalImprove to obtain a constant approximation O(OPT) as long as CONN/OPT = Omega(1). This yields the first flow-based algorithm. Moreover, its performance strictly outperforms the ones based on random walks and surprisingly matches that of the best known global algorithm, which is SDP-based, in this parameter regime [MMV12]. Finally, our results show that spectral methods are not the only viable approach to the construction of local graph partitioning algorithm and open door to the study of algorithms with even better approximation and locality guarantees.
A Secure Distributed Authentication scheme based on CRT-VSS and Trusted Computing in MANET
Venue: arXiv cs.CR 2013
Year: 2013

With the rapid development of MANET, secure and practical authentication is becoming increasingly important. The existing works perform the research from two aspects, i.e., (a)secure key division and distributed storage, (b)secure distributed authentication. But there still exist several unsolved problems. Specifically, it may suffer from cheating problems and fault authentication attack, which can result in authentication failure and DoS attack towards authentication service. Besides, most existing schemes are not with satisfactory efficiency due to exponential arithmetic based on Shamir's scheme. In this paper, we explore the property of verifiable secret sharing(VSS) schemes with Chinese Remainder Theorem (CRT), then propose a secret key distributed storage scheme based on CRT-VSS and trusted computing for MANET. Specifically, we utilize trusted computing technology to solve two existing cheating problems in secret sharing area before. After that, we do the analysis of homomorphism property with CRT-VSS and design the corresponding shares-product sharing scheme with better concision. On such basis, a secure distributed Elliptic Curve-Digital Signature Standard signature (ECC-DSS) authentication scheme based on CRT-VSS scheme and trusted computing is proposed. Furthermore, as an important property of authentication scheme, we discuss the refreshing property of CRT-VSS and do thorough comparisons with Shamir's scheme. Finally, we provide formal guarantees towards our schemes proposed in this paper.
A New Approach to the Solution of Economic Dispatch Using Particle Swarm Optimization with Simulated Annealing
Venue: arXiv cs.CE 2013
Year: 2013

A new approach to the solution of Economic Dispatch using Particle Swarm Optimization is presented. It is the progression of allocating production amongst the dedicated units such that the restriction forced are fulfilled and the power needs are reduced. More just, the soft computing method has received supplementary concentration and was used in a quantity of successful and sensible applications. Here, an attempt has been made to find out the minimum cost by using Particle Swarm Optimization Algorithm using the data of three generating units. In this work, data has been taken such as the loss coefficients with the max-min power limit and cost function. PSO and Simulated Annealing are functional to put out the least amount for dissimilar energy requirements. When the outputs are compared with the conventional method, PSO seems to give an improved result with enhanced convergence feature. All the methods are executed in MATLAB environment. The effectiveness and feasibility of the proposed method were demonstrated by three generating units case study. Output gives hopeful results, signifying that the projected method of calculation is competent of economically formative advanced eminence solutions addressing economic dispatch problems.
Optimal competitiveness for Symmetric Rectilinear Steiner Arborescence and related problems
Venue: arXiv cs.DC 2013
Year: 2013

We present optimal competitive algorithms for two interrelated known problems involving Steiner Arborescence. One is the continuous problem of the Symmetric Rectilinear Steiner Arborescence (SRSA), studied by Berman and Coulston. A very related, but discrete problem (studied separately in the past) is the online Multimedia Content Delivery (MCD) problem on line networks, presented originally by Papadimitriu, Ramanathan, and Rangan. An efficient content delivery was modeled as a low cost Steiner arborescence in a grid of network*time they defined. We study here the version studied by Charikar, Halperin, and Motwani (who used the same problem definitions, but removed some constraints on the inputs). The bounds on the competitive ratios introduced separately in the above papers are similar for the two problems: O(log N) for the continuous problem and O(log n) for the network problem, where N was the number of terminals to serve, and n was the size of the network. The lower bounds were Omega(sqrt{log N}) and Omega(sqrt{log n}) correspondingly. Berman and Coulston conjectured that both the upper bound and the lower bound could be improved. We disprove this conjecture and close these quadratic gaps for both problems. We first present an O(sqrt{log n}) deterministic competitive algorithm for MCD on the line, matching the lower bound. We then translate this algorithm to become a competitive optimal algorithm O(sqrt{log N}) for SRSA. Finally, we translate the latter back to solve MCD problem, this time competitive optimally even in the case that the number of requests is small (that is, O(min{sqrt{log n},sqrt{log N}})). We also present a Omega(sqrt[3]{log n}) lower bound on the competitiveness of any randomized algorithm. Some of the techniques may be useful in other contexts.